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matlab2tikz / matlab2tikz

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ConstantLine (xline yline) unsupported

4
LeoRauschenberger
LeoRauschenberger commented Jan 8, 2020

ConstantLine was introduced in 2018b:
https://de.mathworks.com/help/matlab/ref/matlab.graphics.chart.decoration.constantline-properties.html

when using for example:
xline(4)
This error appears:
`Error using matlab2tikz>handleAllChildren (line 730)
I don't know how to handle this object: constantline
Error in matlab2tikz>drawAxes (line 880)
[m2t, childrenEnvs] = handleAllChildren(m2

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+0.0.1 HG2 feature request good first issue

casadi / casadi

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CasADi is a symbolic framework for numeric optimization implementing automatic differentiation in forward and reverse modes on sparse matrix-valued computational graphs. It supports self-contained C-code generation and interfaces state-of-the-art codes such as SUNDIALS, IPOPT etc. It can be used from C++, Python or Matlab/Octave.

python c-plus-plus library modular optimization matlab mathematics nonlinear octave numerical-calculations scientific-computing derivatives code-generation parameter-estimation academic-project optimal-control symbolic-manipulation algorithmic-differentation nonlinear-programming
  • Updated Jul 22, 2021
  • C++

TheAlgorithms / MATLAB-Octave

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Add more algorithms!

12
cozek
cozek commented Oct 10, 2019

EDIT 6/10/20: If you are making a PR for hacktoberfest, please say so in your PR description so that I can add
the hacktoberfest-accepted label.

This repo needs more algorithms. If you see any missing algorithms, kindly contribute.
Hackotberfest participants are welcome!
I will list some of the algorithms that are up for grabs. However, please check if the algorithm
is already in ou

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good first issue hacktoberfest help wanted

cbm755 / octsympy

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octave symbolic unique

1
Micky71
Micky71 commented May 27, 2021

syms a;

unique([a,a]) works fine, but

unique([a])

leads to the following error:
error: Python exception: UnboundLocalError: local variable ‘s’ referenced before assignment
occurred at line 1 of the Python code block:
return sp.Matrix([list(uniq(*ins))]),
error: called from
pycall_sympy_ at line 178 column 7
unique at line 55 column 5

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bug good first issue

liquidSVM / liquidSVM

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Support vector machines (SVMs) and related kernel-based learning algorithms are a well-known class of machine learning algorithms, for non-parametric classification and regression. liquidSVM is an implementation of SVMs whose key features are: fully integrated hyper-parameter selection, extreme speed on both small and large data sets, full flexibility for experts, and inclusion of a variety of different learning scenarios: multi-class classification, ROC, and Neyman-Pearson learning, and least-squares, quantile, and expectile regression.

python c-plus-plus machine-learning r apache-spark matlab svm ml regression octave classification rstats r-package quantile-regression expectile-regression
  • Updated Feb 20, 2020
  • C++

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